To obtain solutions with high fidelity a properly constrained problem must necessarily exist. The greater the constraints the more exact the solution. 2 +2 is a highly constrained problem with an exact solution. x + y = is a poorly constrained problem with an infinite number of solutions.
constraints also need to be aligned with objectives otherwise solutions have no real value, they are just solutions to a given well constrained problem.
Example, fitting 37-38s with the objective being articulation and wheeling.
first, Some constraints are more fixed than others. A proper understanding of the constraints is necessary for a good solution. Once again infinite solutions may exist. wheel offset is NOT a free constrain for our platform. For achieving an oem steering moment arm, the wheel offset should be +18 mm. This is a real constraint since steering system is a weak point. Can this constraint be loosened some? sure. But -6 m is a bit much when other solutions exist.
Some other constraints include strut modifications. They also have constraints but perhaps are more free. Strut designs such that maximum suspension lift can be achieved within the control arm geometric constraints, both front and rear. Such coilover designs currently exist off the shelf. Many pages on this in this thread
body lift is also available within constraints, perhaps max of 1-2”. This can be used to minimize CG and reduce suspension lift if possible.
Finally interference constraints can also be freed up if you are willing to use a sawsall. Crash bars and mounts are the obvious ones but others may also be there. I personally can’t see any solution that has rock sliders as an interference constraint. Cut them or replace.
Those are my objectives and constraints. Most definitely a completely different solution than alternative constraints applied to the same problem.
Without a proper understanding of the constraints, poor solutions are obtained for a given set of objectives.
I question whether ChatGPT is able to take a basic set of objectives and apply the most appropriate constraints that lead to the optimal solution. If you apply the constraints for ChatGPT then it has not achieved anything more than data mining. Which can be extremely useful but only if the data set is valid.
written by a more competent ChatGPT, a human.
constraints also need to be aligned with objectives otherwise solutions have no real value, they are just solutions to a given well constrained problem.
Example, fitting 37-38s with the objective being articulation and wheeling.
first, Some constraints are more fixed than others. A proper understanding of the constraints is necessary for a good solution. Once again infinite solutions may exist. wheel offset is NOT a free constrain for our platform. For achieving an oem steering moment arm, the wheel offset should be +18 mm. This is a real constraint since steering system is a weak point. Can this constraint be loosened some? sure. But -6 m is a bit much when other solutions exist.
Some other constraints include strut modifications. They also have constraints but perhaps are more free. Strut designs such that maximum suspension lift can be achieved within the control arm geometric constraints, both front and rear. Such coilover designs currently exist off the shelf. Many pages on this in this thread
body lift is also available within constraints, perhaps max of 1-2”. This can be used to minimize CG and reduce suspension lift if possible.
Finally interference constraints can also be freed up if you are willing to use a sawsall. Crash bars and mounts are the obvious ones but others may also be there. I personally can’t see any solution that has rock sliders as an interference constraint. Cut them or replace.
Those are my objectives and constraints. Most definitely a completely different solution than alternative constraints applied to the same problem.
Without a proper understanding of the constraints, poor solutions are obtained for a given set of objectives.
I question whether ChatGPT is able to take a basic set of objectives and apply the most appropriate constraints that lead to the optimal solution. If you apply the constraints for ChatGPT then it has not achieved anything more than data mining. Which can be extremely useful but only if the data set is valid.
written by a more competent ChatGPT, a human.
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